9-13 July 2018
Sofia, Bulgaria
Europe/Sofia timezone

Continuous Analysis Preservation and Streamlining for the ATLAS Experiment

9 Jul 2018, 15:30
Hall 9 (National Palace of Culture)

Hall 9

National Palace of Culture

presentation Track 6 – Machine learning and physics analysis T6 - Machine learning and physics analysis


Lukas Alexander Heinrich (New York University (US))


We present recent work within the ATLAS collaboration to centrally provide tools to facilitate analysis management and highly automated container-based analysis execution in order to both enable non-experts to benefit from these best practices as well as the collaboration to track and re-execute analyses independently, e.g. during their review phase.

Through integration with the ATLAS GLANCE system, users can request a pre-configured, but customizable version control setup, including continuous integration for automated build and testing as well as continuous Linux Container image building for software preservation purposes.

As analyses typically require many individual steps, analysis workflow pipelines can then be defined using such images and the yadage workflow description language. The integration into the workflow exection service REANA allows the interactive or automated reproduction of the main analysis results by orchestrating a large number of container jobs using Kubernetes.

For long-term archival, we present integration with the CERN Analysis Preservation Portal (CAP), where data, analysis repositories, software images and workflows can be stored and indexed for later re-use such as reinterpretations.

Primary authors

Lukas Alexander Heinrich (New York University (US)) Kyle Stuart Cranmer (New York University (US)) Davide Costanzo (University of Sheffield (GB)) Borut Paul Kersevan (Jozef Stefan Institute (SI)) Attila Krasznahorkay (CERN) Kerim Suruliz (University of Sussex (GB))

Presentation Materials